In three-dimensional ultrasound imaging, or volume imaging, the acquisition of a three-dimensional image is accomplished by conducting many two-dimensional scans that slice through the volume of interest. Hence, a multitude of two-dimensional images is acquired that lie next to another. By proper image processing, a three-dimensional image of the volume of interest can be built out of the multitude of two-dimensional images. The three-dimensional information acquired from the multitude of two-dimensional images is displayed in proper form on a display for the user of the ultrasound system.
Further, so-called live three-dimensional imaging, or 4D imaging, is often used in clinical applications. In live three-dimensional imaging, a real-time view on the volume can be acquired enabling a user to view moving parts of the anatomical site, for example a beating heart or else. In the clinical application of live three-dimensional imaging there is sometimes a need to image a relatively small area of the heart such as a single valve, or a septal defect, and there is sometimes the need to image a large area of the heart such as an entire ventricle.
Unlike conventional or normal ultrasound (US), contrast-enhanced ultrasound (CEUS) enables a real-time three-dimensional visualization of the blood flow. This recent modality is gaining more interest as it is harmless for the patient—since no radiation and non-toxic contrast agent may be used—while providing different and useful information. Vascularised organs such as the kidneys or the liver are completely enhanced while their surroundings produce little signal.
Image segmentation is a common task for radiologists. The extracted surface can be used either to quantify the volume of an organ or a tumor, or as a landmark to perform feature-based image registration. However, it is often tedious to manually segment an organ in a 3D image. While quantification and visualization tools are relatively available for 2D images, 3D volumes analysis is often done by hand through tedious procedures impossible to realize in clinical practice. However, such methods do not provide satisfying results. Precise segmentations are therefore needed, but difficult to obtain, especially in ultrasound images which are corrupted by a lot of noise and various artifacts.
Document US 2009/0326363 A1 discloses a method for the registration of medical images. The method registers a previously obtained volume onto an ultrasound volume during an ultrasound procedure to produce a multimodal image. The multimodal image may be used to guide a medical procedure. The multimodal image includes magnetic resonance imaging (MRI) and/or magnetic resonance spectroscopy imaging (MRSI) information presented in the framework of a transrectal ultrasonography (TRUS) image during a TRUS procedure.
There is a need for improved automatic or at least computer-aided segmentation tools.